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POST
Search Content
Performs vector-similarity search over project content (entities, comments, and chat messages) using AI embeddings. Returns the most semantically relevant results for the given query. Requires a paid plan with semantic search enabled.

Body Parameters

string
required
The natural language search query.
string[]
default:"[\"entity\", \"comment\", \"message\"]"
Content types to search. Any combination of entity, comment, message.
string
Restrict search to a specific space.
string
Restrict message search to a specific conversation.
number
default:"20"
Maximum number of results to return. Maximum 50.

Query Parameters

Space-scoped reputation

This endpoint has a space in context, so it accepts the opt-in reputation params. They add a spaceReputation field to each result record’s populated user, alongside the always-present reputation total. Requires the reputation bundle. See the Reputation data model for the full contract.
string
Adds spaceReputation to each returned user. One of: a space <uuid> (that space’s bucket), none (the project-general bucket), or context (the space derived from this request’s context — per-row on lists). The empty string and the legacy general / null aliases are rejected (400). Missing buckets read as 0.
boolean
Only honored with an explicit space <uuid>. When true, spaceReputation is the subtree sum — the space plus all of its descendants (the root space’s own bucket included). Ignored for none; not allowed with context.

Response

Returns an array of result objects ordered by similarity (highest first):
Each result includes:
  • sourceType — one of "entity", "comment", or "message", indicating which type of record was matched.
  • similarity — cosine similarity score between the query and the matched content.
  • record — the fully populated entity, comment, or chat message object.

Error Responses